dc.contributor.author | Tatar, Güner | |
dc.contributor.author | Bayar, Salih | |
dc.contributor.author | Çiçek, İhsan | |
dc.date.accessioned | 2023-12-22T07:20:52Z | |
dc.date.available | 2023-12-22T07:20:52Z | |
dc.date.issued | 2023 | en_US |
dc.identifier.citation | TATAR, Güner, Salih BAYAR & İhsan ÇİÇEK. "Performance Evaluation of Real-Time Video Processing Edge Detection on Various Platforms". 2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT), (2023). | en_US |
dc.identifier.uri | https://hdl.handle.net/11352/4690 | |
dc.description.abstract | As real-time video processing applications grow in
complexity, they demand higher performance. Achieving such
a performance must involve a delicate balance between design
constraints and optimization of performance criteria. A vital
aspect of this balance is the integration of application-specific
accelerator designs to boost computational efficiency. To illustrate
this, we applied Laplacian High-Pass filtering operations on
real-time video signals across three hardware platforms an
ARM processor, an ARM+FPGA-based SoC, and a single-core
Intel i7 processor. We further analyzed these platforms’ priceperformance ratios. Our research revealed that the ARM+FPGAbased SoC executed the filtering algorithms 23.124 times faster
than the ARM processor and 1.969 times faster than the Intel i7
processor. Additionally, the ARM+FPGA-based SoC also showed
the highest price-performance efficiency. To offer readers a more
visual understanding, we include a resource utilization graph
for the SoC hardware accelerator development board, thus
demonstrating the efficiency of each platform tested. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | 10.1109/AICT59525.2023.10313150 | en_US |
dc.rights | info:eu-repo/semantics/embargoedAccess | en_US |
dc.subject | Video Processing | en_US |
dc.subject | OpenCV | en_US |
dc.subject | PYNQ-Z1 SoC | en_US |
dc.subject | FPGA Vision | en_US |
dc.subject | Overlay Design | en_US |
dc.subject | Pipeline Architecture | en_US |
dc.subject | Hardware Accelerator | en_US |
dc.title | Performance Evaluation of Real-Time Video Processing Edge Detection on Various Platforms | en_US |
dc.type | conferenceObject | en_US |
dc.relation.journal | 2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT) | en_US |
dc.contributor.department | FSM Vakıf Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
dc.contributor.authorID | https://orcid.org/0000-0002-3664-1366 | en_US |
dc.contributor.authorID | https://orcid.org/0000-0002-4600-1880 | en_US |
dc.contributor.authorID | https://orcid.org/0000-0002-7881-1263 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.contributor.institutionauthor | Tatar, Güner | |